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T. Hoefler:
  Performance Modeling for Future Computing Technologies
(Presentation  Jun. 2018) Invited talk at 60 years of CS @ Tsinghua celebration
AbstractWe are close to a phasechange in the computing industry. The demand for computing power is steadily increasing with the advent of (deep) learning and other highperformance computing techniques. However, the end of Dennard scaling and Moore's law force us to design for parallelism and specialization to improve compute performance. The complexity of programming is enormous and we propose the use of mathematical models to understand the performance requirements of practical algorithms. We first show pitfalls of seemingly simple performance measurements, followed by a methodology to design closetooptimal programs. We also showcase a mathematical system design methodology for highperformance networks. All these examples testify to the value of modeling in practical highperformance computing. We assume that a broader use of these techniques and the development of a solid theory for parallel performance will lead to deep insights at many fronts.
Documentsdownload slides:   BibTeX  @misc{modelingtsinghua, author={T. Hoefler}, title={{Performance Modeling for Future Computing Technologies}}, year={2018}, month={Jun.}, source={http://www.unixer.de/~htor/publications/}, } 

